Optimization of engineering solutions used to develop the underground spaces of existing buildings

Introduction. The article deals with the optimization of engineering solutions applied in the course of arrangement of additional underground spaces under existing buildings. The decreasing number of unoccupied spaces in the central areas of developing cities and the fact that the expansion of spaces under existing buildings allows the city to effectively and organically develop its territories explain the relevance of this research. Materials and methods. The authors apply the central composite Box design, that is used to construct second order polynomials to make a plan of a two-factor composite (rotatable) experiment with a quadratic model. To solve this problem, the following software programmes were used: Gradient 3.1; Mathematica. The object of numerical calculations is a frameless 3-storey building. The structures, used to calculate the labour intensity of the work performed, included piles, ground beams, and foundation grillages. The weight of metal structures and the labour intensity were the parameters to be studied. Results. A mathematical model was developed and dependence functions of the studied parameters, affecting the reinforcement of an existing building during the redevelopment of its underground space, were obtained. Optimal values of (1) weight of metal structures and (2) the labour intensity, reducing the total cost of the proposed technology, were identified. The Mathe­matica software package was applied to identify the optimal beam spacing that varied from 1.2 to 1.5 m. Conclusions. The function, obtained by the authors, describes the curve showing dependence between the following two parameters: the weight of metal structures, used to reinforce the building, and the labour intensity of installation work. Optimal values of the studied parameters, ensuring minimal weight and labour intensity, are identified to reduce the total weight of metal structures, used to reinforce the existing building and reduce the overall cost of the proposed technology.